COVID-19 self-testing using antigen rapid diagnostic tests: Feasibility evaluation among health-care workers and general population in Malawi

Background COVID-19 testing is critical for identifying cases to prevent transmission. COVID-19 self-testing has the potential to increase diagnostic testing capacity and to expand access to hard-to-reach areas in low-and-middle-income countries. We investigated the feasibility and acceptability of COVID-19 self-sampling and self-testing using SARS-CoV-2 Antigen-Rapid Diagnostic Tests (Ag-RDTs). Methods From July 2021 to February 2022, we conducted a mixed-methods cross-sectional study examining self-sampling and self-testing using Standard Q and Panbio COVID-19 Ag Rapid Test Device in Urban and rural Blantyre, Malawi. Health care workers and adults (18y+) in the general population were non-randomly sampled. Results Overall, 1,330 participants were enrolled of whom 674 (56.0%) were female and 656 (54.0%) were male with 664 for self-sampling and 666 for self-testing. Mean age was 30.7y (standard deviation [SD] 9.6). Self-sampling usability threshold for Standard Q was 273/333 (82.0%: 95% CI 77.4% to 86.0%) and 261/331 (78.8%: 95% CI 74.1% to 83.1%) for Panbio. Self-testing threshold was 276/335 (82.4%: 95% CI 77.9% to 86.3%) and 300/332 (90.4%: 95% CI 86.7% to 93.3%) for Standard Q and Panbio, respectively. Agreement between self-sample results and professional test results was 325/325 (100%) and 322/322 (100%) for Standard Q and Panbio, respectively. For self-testing, agreement was 332/333 (99.7%: 95% CI 98.3 to 100%) for Standard Q and 330/330 (100%: 95% CI 99.8 to 100%) for Panbio. Odds of achieving self-sampling threshold increased if the participant was recruited from an urban site (odds ratio [OR] 2.15 95% CI 1.44 to 3.23, P < .01. Compared to participants with primary school education those with secondary and tertiary achieved higher self-testing threshold OR 1.88 (95% CI 1.17 to 3.01), P = .01 and 4.05 (95% CI 1.20 to13.63), P = .02, respectively. Conclusions One of the first studies to demonstrate high feasibility and acceptability of self-testing using SARS-CoV-2 Ag-RDTs among general and health-care worker populations in low- and middle-income countries potentially supporting large scale-up. Further research is warranted to provide optimal delivery strategies of self-testing.

CoV-2 self-testing has the potential to increase diagnostic testing capacity and to expand access 27 to hard-to-reach areas in low-and-middle-income countries. We investigated the feasibility and 28 acceptability of COVID-19 self-sampling and self-testing using SARS-CoV-2 Antigen-Rapid 29 Diagnostic Tests (Ag-RDTs). SARS-CoV-2 rapid antigen tests (Ag-RDTs) are recommended to complement nucleic acid 61 amplification tests (NAAT) for diagnosis [7], which in resource-limited settings are often hard to 62 implement because they require specialised skills and limited centralized laboratory capacity, 63 associated with long turnaround times, and high costs to both the health system and patients.

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COVID-19 self-testing was strongly recommended by the World Health Organization (WHO) in 65 March 2022 as an additional strategy to complement professionally administered testing 66 services.
[8] Self-testing, which has been successfully used in other disease areas such as HIV 67 where uptake is ubiquitously high including among hard to reach and key populations.[9-11] In 68 general, COVID-19 self-testing has the potential to increase diagnostic capacity for COVID-19 69 and reduce access barriers as well as prevailing inequalities due to ease of distribution and being 70 extremely convenient.
[12] However, COVID-19 self-testing has so far been widely implemented 71 and made available in high income countries. [12][13][14] As with HIV self-testing, lack of linkage 72 for next steps with COVID-19 is a potential concern due to stigma, loss of economic 73 opportunities due to isolation implications, and fear of complications including death. Being able to self-test rests on the assumption that individuals would be able to take their own 75 sample (self-sampling).
[15] However, in settings with low exposure to technology and the ability 76 to correctly follow instructions such assumptions may be faulty.
[16] Thus, early work including 77 optimization of instructions for use through iterative cognitive interviews is essential to ensure 78 correct use of self-tests.

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Study design 83 A mixed-methods cross-sectional study examining self-sampling and self-testing for COVID-19 84 using STANDARD Q COVID-19 Ag Test (SD Biosensor) and Panbio COVID-19 Ag Rapid Test 85 Device (Abbott Rapid Diagnostics). We conducted the study under five components. These are: 86 cognitive interviews to refine instructions for use (IFUs) for self-sampling, observational cross-87 sectional study of self-sampling, cognitive interviews to refine instructions for use for self-testing, 88 observational cross-sectional study of self-testing, and in-depth interviews (IDIs) to understand 89 participant views on self-sampling and self-testing. We recruited health care workers and members of the general public from the recruitment sites.

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To be eligible, participants needed to be 18 years or older, feeling well enough to comfortably 98 conduct study activities, not having recent history of excessive nose bleeds, and having given 99 consent. All health workers from the two health facilities were offered the choice to participate in 100 the study with exclusion only done if ineligible. An additional eligibility criteria which was later 101 relaxed due to scarcity of participants with waning wave concerned individuals being on the list 102 to be tested for COVID-19 by the national systems. General public participants were 103 systematically sampled from outpatient departments. An anterior nasal swab for COVID-19 was 104 done for both self-sampling and self-testing following a short in-person demonstration by a 105 member of staff.

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Participants were observed in-person during self-sampling and self-testing, and a checklist (S1-107 S4 appendix) was completed to document whether each task was done correctly. A trained 108 researcher then tested the collected sample using a COVID-19 Ag RDT during the self-sampling instructions during the self-sampling process for each kit. Correct self-sampling was referred to 118 as self-sampling accuracy. The second primary outcome was the percentage of participants who 119 attained a usability threshold for self-testing, defined as correct execution of all critical 120 instructions during the self-testing process. Correct self-testing was referred to as self-testing 121 accuracy. User views regarding self-sampling and self-testing were the main outcomes from the The main source of bias is in the assessment by the research staff using a checklist of the 135 performance of the participant on the IFU. A staff member who was more punitive may have 136 harshly rated performance as incorrect while a more forgiving one may have rated performance 137 differently. However, the fact that more than seven staff members were involved in the rating 138 may have minimized such bias.

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Study size 140 We aimed to recruit and purposively sample 120 participants for cognitive interviews for self-141 sampling and self-testing for both test kits. For self-sampling and self-testing, we conservatively 142 assumed that 70% to 80% of participants will be able to correctly follow instructions and self-143 sample or self-test for COVID-19. For the sample proportion to be estimated to within +/-0.05 144 (5%) using the 95% confidence level, a sample of 323 participants were required. Thus, a total of 145 1,320 participants were needed: 330 per test kit for self-sampling and self-testing. A purposive 146 sample of 120 participants was needed for the IDIs: 60 self-sampling and 60 self-testing 147 participants.

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Quantitative variables 149 A binary variable was generated for the first and secondary primary outcomes of achieving the

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Participants and Descriptive data 181 A total of 120 participants were recruited for self-sampling and self-testing cognitive interviews.

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Of 723 screened for eligibility 664 (91.8%) were recruited for self-sampling with mean age of 183 31.4y (standard deviation [SD]: 9.8) and 357/664 (53.8%) were male (  Up to 95% of the critical steps were performed correctly on either test kit for both self-sampling 215 and self-testing (Table 4).
216 The odds of self-sampling accuracy increased 2-fold for participants from QECH compared to 220 participants from Lirangwe primary health centre odds ratio (OR) 2.15 (95% CI 1.44 to 3.23, P < 221 0.1 (Table 5). There appeared to be a linear trend towards increased odds of attaining self-testing 222 accuracy with increasing levels of education, P for trend 0.01.  Table). Up to 90.7% Standard Q and 96.1% Panbio participants 232 found instructions "not at all hard" when asked on exit interviews (S6 Table). useful for specific settings and userssuch as older age groups and those with lower literacy.

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Lessons learned from introduction and scale-up of other self-testing approaches such as HIV and

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HCV may be appliable here to accelerate adaptation plans and efforts in LMIC.

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Conclusions 275 This is one the first studies to demonstrate high usability and acceptability self-testing using 276 SARS-CoV-2 Ag-RDTs among both general and health-care worker populations in low-and 277 middle-income countries. While most users collected their own samples and self-tested with 278 ease, participants noted demonstrations were helpful and could be important in some settings and populations, such as older age groups and those with low literacy levels. COVID-19 self-testing 280 is an important strategy for further consideration as it may be a promising tool for increasing 281 access to and uptake of COVID-19 testing services as well as strategies to reduce transmission 282 and linkage to further care, treatment and support services.

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The authors would like to thank all study participants, participating health facilities, and project 285 team members for their contributions to the successful completion of this project.